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Bedside tracking of functional autonomic age in preterm infants
Kartik K Iyer1, Unnah Leitner2,3, Vito Giordano4
1QIMR Berghofer Medical Research Institute, Brisbane, QLD, 4006, Australia. Kartik.iyer@qimrberghofer.edu.au.
Insights
We developed a tool using heart rate variability (HRV) to track autonomic maturation in preterm infants. This functional autonomic age (FAA) closely correlates with postmenstrual age and brain development, aiding bedside monitoring.
Area of Science:
- Neonatal physiology and developmental pediatrics.
- Cardiovascular monitoring and autonomic nervous system function.
- Machine learning applications in clinical assessment.
Background:
- Preterm birth poses long-term health risks for infants, necessitating early monitoring and intervention.
- Autonomic maturation is a critical developmental process in preterm infants.
- Current bedside monitoring lacks specialized tools for assessing autonomic development.
Purpose of the Study:
- To develop a tool for tracking autonomic maturation in preterm infants using heart rate variability (HRV).
- To assess the correlation of this tool with postmenstrual age (PMA) and functional brain age (FBA).
- To provide a method for bedside monitoring of autonomic development in the NICU.
Main Methods:
- Longitudinal electrocardiogram (ECG) recordings from 67 preterm infants (26-38 weeks PMA).
- Supervised machine learning to compute functional autonomic age (FAA) from 50 HRV features.
- Assessed FAA correlation with PMA, clinical outcomes, and functional brain age (FBA) derived from EEG.
Main Results:
- FAA strongly correlated with PMA (r=0.86, MAE=1.66 weeks).
- FAA accurately estimated FBA (MAE=1.58 weeks).
- FAA-PMA relationship was not confounded by sex, birth weight, or common neonatal morbidities.
Conclusions:
- Functional autonomic age (FAA) derived from ECG offers a bedside tool for estimating autonomic maturation in preterm infants.
- FAA provides a specialized view of cardiovascular health and maturational trajectories.
- This tool aids in monitoring preterm infants during intensive care.
Background:
Preterm birth predisposes infants to adverse outcomes that, without early intervention, impacts their long-term health. To assist bedside monitoring, we developed a tool to track the autonomic maturation of the preterm by assessing heart rate variability (HRV) changes during intensive care.
Methods:
Electrocardiogram (ECG) recordings were longitudinally recorded in 67 infants (26-38 weeks postmenstrual age (PMA)). Supervised machine learning was used to generate a functional autonomic age (FAA), by combining 50 computed HRV features from successive 5-minute ECG epochs (median of 23 epochs per infant). Performance of the FAA was assessed by correlation to PMA, clinical outcomes and the infant's functional brain age (FBA), an index of maturation derived from the electroencephalogram.
Results:
The FAA was strongly correlated to PMA (r = 0.86, 95% CI: 0.83-0.93) with a mean absolute error (MAE) of 1.66 weeks and also accurately estimated FBA (MAE = 1.58 weeks, n = 54 infants). The relationship between PMA and FAA was not confounded by neurodevelopmental outcome (p = 0.18, n = 45), sex (p = 0.88, n = 56), patent ductus arteriosus (p = 0.08, n = 56), IVH (p = 0.63, n = 56) or body weight at birth (p = 0.95, n = 56).
Conclusions:
The FAA, an index derived from the ubiquitous ECG signal, offers direct avenues towards estimating autonomic maturation at the bedside during intensive care monitoring.
Impact:
The development of a tool to track functional autonomic age in preterm infants based on heart rate variability features in the electrocardiogram provides a rapid and specialized view of autonomic maturation at the bedside. Functional autonomic age is linked closely to postmenstrual age and central nervous system function response, as determined by its relationship to functional brain age from the electroencephalogram. Tracking functional autonomic age during neonatal intensive care unit monitoring offers a unique insight into cardiovascular health in infants born extremely preterm and their maturational trajectories to term age.
